Reference Intervals for Absolute and Percentage Immature Platelet Fraction using the

Sysmex XN-10 Automated Haematology Analyser in a UK Population

Usman Ali, Gavin Knight, Roz Gibbs and Dimitris A. Tsisikas

Abstract

Background: Immature platelet fraction (IPF) estimation is a non-invasive and sensitive test

that is available on recently introduced Sysmex XN-series of automated haematology analysers. It

is a direct cellular indicator of thrombopoiesis. The aim of this study was to establish

reference intervals for IPF, for both absolute (A-IPF) and percentage (%-IPF) measurements.

Materials and Methods: A total of 2366 samples that met the inclusion criteria were assayed for

full blood count on the Sysmex XN-10 and a non-parametric percentile method was used for

calculating the reference intervals.

Results: After the outliers were excluded, the reference interval for %-IPF and A-IPF on Sysmex

XN-10 were 1.6–10.1% and 4.37–23.21 x 109/l in total individuals, respectively. There was a

statistical significance noted between the sexes (P= 0.004) for %-IPF, therefore a sex-specific

reference interval was established, which was 1.8–10.0% for the males and 1.5–10.1% for

females. No significant difference in sex status for A-IPF and age status for both %-IPF and A-

IPF was observed. A very poor correlation was estimated between age versus %-IPF, ρ=0.0156,

and age versus A-IPF, ρ=-0.0023, indicating that there is no overall biological relationship

between age and these parameters. As expected, a strong correlation between %-IPF and A-IPF

was noted which could be attributed to their inter-relatedness.

Conclusion: This large-scale study showed comparable reference intervals with the previous

studies for %-IPF and A-IPF in a UK population. It found the need to establish sex-specific

reference intervals for %-IPF, but not for A-IPF, whereas reference intervals were found to be

stable across the age range.

Keywords: reference values, blood platelet, haematology, thrombocytopenia, blood cell count,

haematologic tests, haematologic diseases, clinical laboratory techniques, clinical laboratory

services, United Kingdom

Introduction

Ingram and Coopersmith first showed that the number of immature platelets increase following

acute blood loss [1]. Using a new methylene blue dye, these immature platelets demonstrated

coarse, punctate, condensations [reticulum; thus called reticulated platelets (RP)] and are

considered analogous to reticulocytes. Two decades later, it was reported that flow cytometry could

detect platelet nucleic acid in RP using a dye that was named ‘thiazole orange’ [2]. Subsequent

reports thus focused on flow cytometric analysis of these RNA-rich RPs using RNA binding dyes

to provide information on thrombopoietic activity [3] in a variety of conditions such as:

thrombocytopenia [4-10], thrombocytosis [11,12], thrombo-embolic disorders [13,14], hereditary

platelet diseases [15,16], following stem cell transplantation [17-20], hyperthyroidism [21], kidney

disease [22-24], preeclampsia [25], and thrombocytopenic and healthy neonates [26,27].

Accordingly, RP became reliably expressed as the immature platelet fraction (IPF) which replaced

labour-intensive manual procedures and time consuming general flow cytometry. These studies

concluded that IPF is a useful, non-invasive, marker for megakaryopoietic activity [28].

In current clinical practice, %-IPF is measured by different haematology analysers ranging from

Sysmex XE-series to XN-series [29]. The Sysmex XE-2100 (Sysmex, Kobe, Japan) was introduced

in 1999 [30]. Subsequently, this analyser underwent a number of upgrades, including an automated

method for measuring %-IPF, using flow cytometry [31]. In 2007, the Sysmex XE-5000 was

launched with additional parameters [32]. A more advanced XN Modular analyser was introduced

in 2011 which was similar to the previous XE-series instruments measuring red cell parameters

and impedance platelets in the same way. Four new channels were introduced including a

fluorescent platelet (PLT-F) channel which provided a better sensitivity and specificity for

measuring %-IPF compared to the previous versions of Sysmex haematology analysers [32]. IPF

can be reported as both the percentage of immature platelets (%-IPF), which the analyser generates,

as well as absolute-IPF (A-IPF), which is a calculated measurement using both the platelet count

and %-IPF [33].

Earlier reference intervals that were established using the XE-series may be invalid for the XN-

series of haematology analysers. More recent studies conducted in China [29] and Korea [34] have

used the XN-series, but have reported different reference intervals which may be associated with

racial and ethnic variation. The aim of the present study, which is the largest study to date, was to

establish new reference intervals for A-IPF and %-IPF in a UK population, for the first time, using

the Sysmex XN-10 automated haematology analyser.

Materials and Methods

Sample Requirement and Inclusion Criteria

Samples of venous whole-blood collected in ethylenediaminetetraacetic acid K2 (EDTA K2)

Vacutainer tubes and received from primary care providers in the Department of Haematology at

Homerton University Hospital were analysed on Sysmex XN-10. To minimise variations due to

sample aging, all tests were completed within 12 hours of collection. A total of 2366 samples with

routinely reported FBC parameters within the reference range were assayed by selecting PLT-F

mode on the Sysmex XN-10. All samples that met the following inclusion criteria were included

in this study: (i) haemoglobin (Hb) 115–165 g/L [females] and 130–180 g/L [males]; (ii) red blood

count (RBC) 3.80–5.80 x 1012/L [females] and 4.50–6.50 x 1012/L [males]; (iii) haematocrit (HCT)

0.37–0.47 L/L [females] and 0.40–0.54 L/L [males]; (iv) mean cell volume (MCV) 80–98 fL; (v)

mean cell haemoglobin (MCH) 27–32 pg;(vi) mean cell haemoglobin concentration (MCHC) 310–

350 g/L; (vii) red blood cell distribution width (RDW) 10–14%; (viii) platelet count (PLT) 150–

400 x 109/L; (ix) white blood count (WBC) 4.0–11.0 x 109/L; (x) neutrophil count (NEUT) 2.0–

7.5 x 109/L; (xi) lymphocyte count (LYMPH) 1.0–4.0 x 109/L; (xii) monocyte count (MONO) 0.2–

1.0 x 109/L; (xiii) eosinophil count (EO) 0.0–0.4 x 109/L; and (xiv) basophil count (BASO) 0.0–

0.1 x 109/L. Daily and weekly internal quality procedures were used for validating the quality of

the results and imprecision was kept minimal with excellent intra-assay coefficients of variability

(CV) of < 2% for 11 repeat analysis cycles (precision check). The study received a favourable

opinion from the National Research Ethics Service (NRES).

Measurement of immature platelets

EDTA K2 anticoagulated, whole-blood, samples were measured on the Sysmex XN-10 analyser

(Sysmex, Kobe, Japan) which is a widely used, routine, fully-automated haematology analyser.

Compared to its previous versions, this analyser uses different principles, channels, and reagents

with improved sensitivity and specificity for %-IPF measurement [32]. In addition to impedance

(PLT-I) and optic (PLT-O) methods for measuring platelet counts, the Sysmex XN-10 has a novel

PLT-F-channel dedicated to measuring mature and immature platelets (Figure 1). This channel was

introduced to improve the gating of platelets to achieve a more accurate platelet count (PLT-F),

using the new fluorescent method, and %-IPF. The analyser uses an algorithm to determine which

platelet count to use – impedance (PLT-I), optical (PLT-O) or the fluorescent method (PLT-F).

The measurement of IPF requires platelet cellular membranes to be perforated by reagents, viz. a

fluorescent dye called oxadine, which stains the nucleic acids [32,35]. IPF enumeration is based on

the principle of haemocytometry and is defined by an algorithm which gates for mature and

immature platelets using side fluorescence (reflecting RNA content), side scatter (intracellular

structure) and forward scatter (cell size) of light. An example of an IPF scattergram is shown in

Figure 1. Immature platelets decrease in RNA content and size as they age, eventually becoming

mature platelets [36]. It has been recently indicated that this RNA is used by platelets for protein

synthesis [37].

Immature platelets – absolute number (A-IPF) and percentage (%-IPF)

IPF is reported in two formats: as the percentage of platelets with above-threshold megakaryocyte-

derived RNA (%-IPF) - a value generated by XE- and XN-series automated haematology analysers

- or the number of immature platelets per unit volume, known as the absolute-IPF (A-IPF). The A-

IPF can be calculated using the formula 100

% CountPlateletIPF ⋅×− [38]. Unlike %-IPF, the A-IPF is

the exact number of immature platelets in the circulation [33].

Statistical analysis

Data was recorded in Excel files. Outliers, defined as values < Q1–1.5(IQR) or > Q3+1.5(IQR),

[39] were checked and eliminated in addition to the data removed following application of the

exclusion criteria. Statistical analysis was performed using Excel 2013 and RStudio (Version

0.99.903) to analyse and graphically represent the data. Histograms were used to determine the

distribution of the data and a normality test was performed using the Kolmogorov-Smirnov test

[40]. Reference intervals were calculated according to the Clinical and Laboratory Standard

Institute (CLSI) guideline EP28-A3c [41]; the non-parametric percentile method (2.5th and 97.5th

percentiles) was used to calculate the reference intervals for %-IPF and A-IPF without making

assumptions about the underlying distribution. This method is superior as no model-based data

fitting is required [42]. Mann-Whitney Test was used to compare male and female counts only.

Kruskal–Wallis one-way analysis of variance was used to compare the test parameters, %-IPF and

A-IPF, with seven age subgroups mainly by decades including: 16-19 years; 20-29 years; 30-39

years; 40-49 years; 50-59 years; 60-69 years; and 70-91 years. Inter-correlations between age, %-

IPF and A-IPF were computed through the Spearman’s correlation which was used to assess the

pairwise relationship between the variables. P values ≤ 0.05 were considered statistically

significant. All data is expressed as 2.5th and 97.5th percentiles (central 95% percentiles) unless

stated otherwise.

Results

A total of 2366 blood samples were collected from individuals with ages range from 16 to 91 years

(765 males and 1527 females). 74 outliers were removed and the remaining 2292 samples were

included in the data analysis. The distribution of both %-IPF and A-IPF (including the subgroups,

data not shown) was non-Gaussian (non-parametric data with P < 0.05), showing left skewed

histograms (Figure 2A and 2B) using visual examination. Unfortunately, it was not possible to

repeat outlying %-IPF and A-IPF results due to the temporal requirements of the study design.

This non-Gaussian distribution was confirmed by the Kolmogorov-Smirnov Z-test [40], which was

used to test all variables for normality. A non-parametric distribution was shown in all subgroups,

thus the Kruskal-Wallis rank sum test, Mann-Whitney U test, and Spearman's rank-order

correlation were used to analyse the data.

The reference interval data for %-IPF and A-IPF for total individuals and sex-divided subgroups

are presented in Table 1. The reference interval for %-IPF was 1.6–10.1% (median %-IPF, 4.4%;

median age, 41 years) in total individuals: 1.8–10.0% in males and 1.5–10.1% in females. The

reference interval for A-IPF was 4.37–23.21 x 109/l (median A-IPF, 10.88 x 109/l; median age, 41

years) in total individuals: 4.66–22.19 x 109/l in males and 4.36–23.49 x 109/l in females.

There was no statistical difference in the reference intervals between males and females for A-IPF

(P= 0.373). Likewise, the Kruskal-Wallis rank sum test showed that there was no overall statistical

significance amongst the seven age subgroups for both %-IPF (P=0.1186) and A-IPF (P= 0.3823),

respectively. Furthermore, a statistical exploration of the correlation between age versus %-IPF –

Spearman ρ=0.0156 (P= 0.454), and age versus A-IPF – Spearman ρ=-0.0023 (P= 0.9115), showed

a statistically insignificant and substantially uncorrelated relationship (Figure 4). However, as

shown in Figures 3 and 4, respectively, the two positive results this study yielded are a statistical

difference in the reference intervals between males and females for %-IPF (P= 0.004) and the

relationship between %-IPF and A-IPF which was statistically significant and highly correlated,

Spearman ρ=0.909 (P < 0.001).

Discussion

After decades of technical challenges in enumerating immature platelets, a real-time IPF diagnostic

tool is available on several automated Sysmex haematology analytical platforms. The clinical

utility of this tool is reported in several conditions [4-27]. Of these, the role of immature platelets

to indicate the mechanism of thrombocytopenia is well recognised [4-10] due to its ability to

differentiate central and peripheral thrombocytopenias [31]. In 2012, an expert group published

recommendations for the management of thrombocytopenia and strongly agreed that decisions to

treat thrombocytopenia should consider, amongst other factors, mechanisms of thrombocytopenia

[43]. To this end, IPF has the potential to offer insight into the underlying mechanisms of

thrombocytopenia, although there is no fundamental UK-based reference interval data currently

available for IPF on the Sysmex XN-series analysers for the purpose of future research and

potential clinical use.

Historically, IPF reference intervals were determined using Sysmex predecessors (Sysmex XE-

2100 or XE-5000) or by using the XN-series analysers comprising individuals from a different

population group [29,34]. Since the Sysmex XN-series utilises different principles for IPF

measurement from its previous version [44], it is important to investigate whether the reference

intervals established on the previous version are valid using the XN-series analysers. A slight

difference was observed between reference intervals across a number of studies (Table 2) using a

range of Sysmex haematology platforms. The reference intervals obtained on the Sysmex XN-

series were generally higher and demonstrated a wider distribution for both %-IPF and A-IPF

compared to the measurement attained on the previous instruments (XE-series analysers)

[29,31,34,45-54].

In this study, we measured IPF in a large number of samples (total n=2366, aged ≥ 16 years old)

with FBC parameters reported within population specific reference ranges. This is the largest study

conducted to date for determining the reference intervals for %-IPF and A-IPF (Table 2). The

reference interval for %-IPF and A-IPF was 1.6–10.1% and 4.37–23.21 x 109/l respectively, when

specimens from both sexes were combined. However, a statistically significant difference between

sexes was apparent and therefore this study established separate reference intervals for sex-specific

subgroups for %-IPF – viz. 1.8–10.0% for males and 1.5–10.1% for females.

Correlation analysis was also performed in this study; a biological relationship between age and

%-IPF or A-IPF is highly unlikely in view of i) the extremely low coefficients of correlation

(Spearman ρ= 0.0156 and ρ= 0.0023), ii) a rather low statistical significance (P = 0.454 and

0.9115), and iii) the large number of data analysed (n=2292). In contrast, a positive association

between %-IPF and A-IPF was confirmed in a highly significant manner, as Figure 4 demonstrates,

with a Spearman ρ= 0.909 (P < 0.001). This was expected as %-IPF values are used to calculate

A-IPF, and therefore, a mathematical inter-relatedness exists between the two parameters.

Overall, the reference intervals achieved in this study compared well with previous studies,

especially for the same series of Sysmex instruments[29,34]. There was a larger variation reported

for %-IPF and A-IPF between our study and those conducted on earlier instruments, most of which

were considerably narrower than our reference intervals. This variation between studies may

represent differences in: the platforms used, populations studied, and methodologies adopted for

determining reference intervals and excluding outliers. Therefore, a standardised application of this

parameter in a clinical setting has been somewhat difficult [55] and a need for instrument-specific

reference intervals is vindicated.

The present study has three limitations. Firstly, the XN-10 used an automated switching algorithm

to report the most accurate platelet count (PLT-I, PLT-O, or PLT-F). This was then used to

calculate the A-IPF instead of setting fluorescent platelets (PLT-F) as a fixed method for this

purpose. This may have slightly increased the A-IPF values because the PLT-I and PLT-O are

known to generate higher platelet counts compared to the PLT-F [56]. Secondly, this study did not

stratify reference intervals according to ethnicity and clinical situations. This may restrict the

application of these reference intervals in different ethnic populations and may impact on its value

in the clinical setting. Thirdly, the influence of biological variation that is essential for analytical

specifications and estimating reference change values was not verified in this study. This may limit

the clinical interpretation of %-IPF and A-IPF [57] and therefore further studies are warranted to

investigate the effects of biological variations.

Conclusion

We have generated reference intervals for both A-IPF and %-IPF in a UK population and found

that for %-IPF there are sex-specific reference intervals, 1.8–10.0% for males and 1.5–10.1% for

females. Reference intervals for A-IPF are independent of sex and likewise reference intervals for

both %-IPF and A-IPF are independent of age. There was a strong correlation between %-IPF and

A-IPF which was expected due to the inter-relatedness of these parameters.

Word Count: 2624

Tables with their headings:

Table 1 Reference intervals for %-IPF and A-IPF on Sysmex XN-10 in samples from apparently

healthy individuals.

n Total Males Females

T

M

F

RI

RI

Median

Age

Range

RI

Median

Age

Range

%-IPF, % 2292 765 1527a 1.6-10.1c 1.8-10.0 4.6 16-91e 1.5-10.1 4.3 16-90f

A-IPF, x 109/l 2292 765 1527b 4.37-23.21d 4.66-22.19 10.71 16-91e 4.36-23.49 10.97 16-90f

A-IPF, absolute immature platelet fraction; %-IPF, percentage immature platelet fraction; T, total;

M, males; F, females; n, sample size; and RI, reference interval. aP =  0.004 vs. males (Mann-

Whitney U-test), decision = rejectnull hypothesis; bP =  0.373 vs. males (Mann-Whitney U-test),

decision = accept null hypothesis; cMedian, 4.4%; dMedian, 10.88 x 109/l ; eMedian, 42 years; and

fMedian, 40 years. The data are expressed as 2.5th and 97.5th percentiles except for age range

which is expressed as a whole range.

Table 2 Comparison of reference intervals for A-IPF and %-IPF using Sysmex analytical platforms

from 2004 to date.

Instrument Population N sex %-IPF A-IPF (x109/l)

Author Year of publication

Sysmex XE-2100 UK 50 Male/Female 1.1-6.1 - Briggs[31] 2004

Sysmex XE-5000 German 309 Male/Female 0.8-6.3 2.3-12.7 Pekelharing[53] 2010

Sysmex XE-2100 South African 60 Male/Female 0.7-5.5 - Mogongoa [54] 2012

Sysmex XE-5000 Brazil 132 Male/Female 0.8-5.6 - Morkis [45] 2016

Sysmex XE-2100 Japan 82 Male/Female 0.5-5.7 1.4-10.4 Takami [48] 2007

Sysmex XE-2100 South Korea 2152 Male/Female 0.5-3.3 1.25-7.02 Ko [49] 2013

Sysmex XE-2100 USA 28 Not stated 0.8-10.1 2.1-19.6 Berny-Lang [46] 2015

Sysmex XE-2100 India 945 Male/Female 0.3-8.7 - Sachdev [50] 2014

Sysmex XE-2100 Italy 229 Male/Female 1.9-4.1 4.2-8.2 Cesari [51] 2013

Sysmex XE-2100 India 100 Not stated 0.7-4.3 - Dadu [52] 2014

Sysmex XE-5000 Denmark 1674 Male/Female 1.3-9.0 - Joergensen [47] 2016

Sysmex XN9000 China 2179 Male/Female 0.4-10.8 0.8-23.0 Yang [29] 2017

Sysmex XN and Sysmex XE-2100

Korea 2104 Male/Female XN: 1.0-7.3 XE: 0.5-3.3

XN: 2.49-15.64 XE: 1.25-7.02

Ko [34] 2015

Sysmex XN9000 UK 2366 Male/Female Total: 1.6-10.1 Males: 1.8-10.0

Females: 1.5-10.1

Total: 4.37-23.21 Current study 2017

Figures:

Figure 1

Figure 2A

Figure 2B

%-IPF

Mature Platelets

Figure 3

Figure 4

n = 765

P = 0.004

%-IPF

A-IPF

Age

n = 1527

Males Females

Figure Legends:

Figure 1. Example of IPF scattergram of PLT-F channel on Sysmex XN-10 showing fluorescence

intensity (RNA content) and forward scatter (size of the platelets)

Figure 2. A. Frequency distribution of %-IPF (n=2366). B. Frequency distribution of A-IPF

(n=2366).

Figure 3. Boxplot of %-IPF data for sex subgroups (n=2292).

Figure 4. Scatter plot matrix illustrating all possible pairwise relationships between variables (age,

%-IPF and A-IPF). Age, years; %-IPF, %; A-IPF, x 109/l. Spearman's rank correlation rho between

age and %-IPF, ρ= 0.0157 (P= 0.454); Spearman's rank correlation rho between age and A-IPF, ρ=

-0.0023 (P= 0.9115); and Spearman's rank correlation rho between %-IPF and A-IPF, ρ= 0.909 (P

< 0.001).

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Acknowledgements

The authors would like to thank the staff at the Department of Haematology at Homerton

University Hospital NHS Foundation Trust for their assistance during this project. Author

contributions: UA designed the project and wrote the paper, RG, GK and DAT co-designed the

project and critically reviewed the manuscript.

Disclosure of conflict of interest: The authors have no conflict of interest to declare.